Wireless Full-Body Capturing for Sport Analytics
Wireless Full Body Motion Capturing for Sport Analytics

With 11 inertial measurement units, the full body motion of a person is tracked during climbing. Potential applications are sports analysis and coaching. Further research will focus on detecting the limbs and body parts in the head mounted camera and use this as additional information for obtaining more precise tracking results. The system has been developed within the European project COGNITO (www.ict-cognito.org)

Wireless Full-Body Capturing for Sport Analytics

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With 11 inertial measurement units, the full body motion of a person is tracked during climbing. Potential applications are sports analysis and coaching. Further research will focus on detecting the limbs and body parts in the head mounted camera and use this as additional information for obtaining more precise tracking results. The system has been developed within the European project COGNITO (www.ict-cognito.org)

Contact: Gabriele.Bleser@dfki.de

Kinect Avatar
We present a novel scanning system for capturing a full 3D human body model using just a single depth camera and no auxiliary equipment. We claim that data captured from a single Kinect is sufficient to produce a good quality full 3D human model. In this setting, the challenges we face are the sensor’s low resolution with random noise and the subject’s non-rigid movement when capturing the data. To overcome these challenges, we develop an improved superresolution algorithm that takes color constraints into account. We then align the super-resolved scans using a combination of automatic rigid and non-rigid registration. As the system is of low price and obtains impressive results in several minutes, full 3D human body scanning technology can now become more accessible to everyday users at home
Kinect Avatar

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We present a novel scanning system for capturing a full 3D human body model using just a single depth camera and no auxiliary equipment. We claim that data captured from a single Kinect is sufficient to produce a good quality full 3D human model. In this setting, the challenges we face are the sensor’s low resolution with random noise and the subject’s non-rigid movement when capturing the data. To overcome these challenges, we develop an improved superresolution algorithm that takes color constraints into account. We then align the super-resolved scans using a combination of automatic rigid and non-rigid registration. As the system is of low price and obtains impressive results in several minutes, full 3D human body scanning technology can now become more accessible to everyday users at home.

OnEye Tracking Framework
OnEye Tracking Framework
OnEye Generic Object Tracking Framework – Tracking examples – 2011-2012 – Clothes tracking (Catwalk sequence 1)

Papers:

  1. “OnEye — Producing and broadcasting generalized interactive video”, Alain Pagani and Christian Bailer and Didier Stricker, Proceedings of the Networked and Electronic Media Summit (NEM Summit), 2013
  2. “A user supported tracking framework for interactive video production”, Christian Bailer and Alain Pagani and Didier Stricker, Proceedings of the European Conference on Visual Media Production (CVMP) 2013
OnEye Tracking Framework

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OnEye Generic Object Tracking Framework – Tracking examples – 2011-2012
Clothes tracking (Catwalk sequence 1)

Papers:
1. “OnEye — Producing and broadcasting generalized interactive video”, Alain Pagani and Christian Bailer and Didier Stricker, Proceedings of the Networked and Electronic Media Summit (NEM Summit), 2013
2.”A user supported tracking framework for interactive video production”, Christian Bailer and Alain Pagani and Didier Stricker, Proceedings of the European Conference on Visual Media Production (CVMP) 2013

Sudplan Project Video
SUDPLAN – Sustainable Urban Development Planner for Climate Change Adaptation

http://www.sudplan.eu

The video describes how the SUDPLAN tool enters the urban planning process, supporting cities adaptation to a rapidly changing climate.

SUDPLAN is a Collaborative Project co-funded by the European Comission within FP7-ICT-2009-6, contract number 247708.

Project partners:
SMHI – Swedish Meteorological and Hydrological Institute
AIT – Austrian Institute of Technology GmbH
cismet GmbH
CENIA – The Czech Environmental Information Agency
Apertum IT AB
DFKI – German Research Center for Artificial Intelligence
SULVF – The Stockholm – Uppsala Air Quality Management Association
City of Wuppertal
TUG – Graz University of Technology

Sudplan Project Video

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SUDPLAN – Sustainable Urban Development Planner for Climate Change Adaptation

http://www.sudplan.eu

The video describes how the SUDPLAN tool enters the urban planning process, supporting cities adaptation to a rapidly changing climate.

SUDPLAN is a Collaborative Project co-funded by the European Comission within FP7-ICT-2009-6, contract number 247708.

Project partners:
SMHI – Swedish Meteorological and Hydrological Institute 
AIT – Austrian Institute of Technology GmbH 
cismet GmbH
CENIA – The Czech Environmental Information Agency
Apertum IT AB
DFKI – German Research Center for Artificial Intelligence
SULVF – The Stockholm – Uppsala Air Quality Management Association 
City of Wuppertal
TUG – Graz University of Technology

3D Reconstructions Representation
3D Reconstructions Representation
A High Quality and Memory Efficient Representation for Image Based 3D Reconstructions Suitable for Realtime Rendering
3D Reconstructions Representation

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A High Quality and Memory Efficient Representation for Image Based 3D Reconstructions Suitable for Realtime Rendering